5 results about "Device Usage" patented technology

A method comprising obtaining, from a master user, a device usage allocation applicable to two or more devices, the two or more devices being associated with another user, the another user being different from the master user, obtaining an aggregate measure of device usage associated with the two or more devices, if the aggregate measure of device usage associated with the two or more devices satisfies a condition relative to the device usage allocation, managing an activity of the two or more devices, and sending a notification to at least one of the two or more devices, the notification for presentation to the another user through a user interface of the at least one of the two or more devices.

Techniques for presenting personalized content to a user are described. A smart home system may determine activity data (including present activity data and device usage history) specific to interactions involving a first device, and generate activity embedding data representing the activity data. The smart home system may also receive a first list content for presentment, and generate a second list of content using the first list and the activity embedding data. The smart home system may send the second list to the first device. The first device may determine a third list of content based on the second list and an identify of a user presently interacting with the first device, such that the third list of content is specific to interactions involving the first device and the user. The first device may then present at least one instance of content represented in the third list.

Verifying that a user is using a device at a pre-designated location between a start time and an end time includes: computing a challenge and an answer as a function of the challenge; generating and storing in a blockchain a commitment including an identity of the user, an identity of the device, the pre-designated location associated with the user, a start time of the device usage, an end time of the device usage, and the computed challenge; generating a visual code for the device to carry the answer; encrypting the generated visual code using a public key of the device, wherein the encrypted visual code can only be decrypted with a private key of the device; and storing the encrypted visual code in the blockchain.

This invention discloses a smart home scene recommendation method and smart home devices. It generates and stores an original scene usage dataset based on smart home device usage data from different users, environmental data at usage times, and publicly available personal characteristic data from each user. A preset feature filtering algorithm is used to select multiple important features with importance metrics greater than a preset threshold from various basic features. A preprocessed scene usage dataset is then selected from the original scene usage dataset based on these important features. Finally, target scene setting parameters matching the current user are determined from the preprocessed scene usage dataset based on the importance metrics of each important feature, and these target scene setting parameters are pushed to the current user's terminal. This allows for more accurate smart home scene recommendations and improves the user experience.

The embodiment of the invention discloses a service recommendation method and device, electronic equipment and a computer readable storage medium, and belongs to the technical field of recommendation. The method comprises: in response to a current key event for a target device, determining service preference information of a target user, and determining use attribute information of the target device, the use attribute information comprising scene information and time period information; and outputting target service recommendation information based on the service preference information and the use attribute information. Thus, when the key operation of the target user is detected, the user service preference and the equipment use attribute can be automatically recognized, intelligent and accurate personalized service recommendation is achieved, the function boundary of physical keys is expanded, the intelligent level of service ecology is effectively improved, and then the interaction efficiency and the user experience are remarkably improved.